Update README.md

antimatter15 · web-flow · commit 7636ddb9e458 · 2023-03-20T22:16:27.000-07:00
diff --git a/README.md b/README.md
@@ -8,37 +8,69 @@ Run a fast ChatGPT-like model locally on your device. The screencast below is no
 
 This combines the [LLaMA foundation model](https://github.com/facebookresearch/llama) with an [open reproduction](https://github.com/tloen/alpaca-lora) of [Stanford Alpaca](https://github.com/tatsu-lab/stanford_alpaca) a fine-tuning of the base model to obey instructions (akin to the [RLHF](https://huggingface.co/blog/rlhf) used to train ChatGPT) and a set of modifications to [llama.cpp](https://github.com/ggerganov/llama.cpp) to add a chat interface. 
 
-## Get started
+## Get Started (7B)
 
-```sh
-git clone https://github.com/antimatter15/alpaca.cpp
-cd alpaca.cpp
+Download the zip file corresponding to your operating system from the [latest release](https://github.com/antimatter15/alpaca.cpp/releases/latest). On Windows, download `alpaca-win.zip`, on Mac (both Intel or ARM) download `alpaca-mac.zip`, and on Linux (x64) download `alpaca-linux.zip`. 
 
-make chat
+Download `ggml-alpaca-7b-q4.bin` and place it in the same folder as the `chat` executable in the zip file. There are several options: 
+
+```
+# Any of these commands will work. 
+curl -o ggml-alpaca-7b-q4.bin -C - https://gateway.estuary.tech/gw/ipfs/QmQ1bf2BTnYxq73MFJWu1B7bQ2UD6qG7D7YDCxhTndVkPC
+curl -o ggml-alpaca-7b-q4.bin -C - https://ipfs.io/ipfs/QmQ1bf2BTnYxq73MFJWu1B7bQ2UD6qG7D7YDCxhTndVkPC
+curl -o ggml-alpaca-7b-q4.bin -C - https://cloudflare-ipfs.com/ipfs/QmQ1bf2BTnYxq73MFJWu1B7bQ2UD6qG7D7YDCxhTndVkPC
+
+# BitTorrent
+magnet:?xt=urn:btih:5aaceaec63b03e51a98f04fd5c42320b2a033010&dn=ggml-alpaca-7b-q4.bin&tr=udp%3A%2F%2Ftracker.opentrackr.org%3A1337%2Fannounce&tr=udp%3A%2F%2Fopentracker.i2p.rocks%3A6969%2Fannounce
+https://btcache.me/torrent/5AACEAEC63B03E51A98F04FD5C42320B2A033010  
+https://torrage.info/torrent.php?h=5aaceaec63b03e51a98f04fd5c42320b2a033010  
+```
+
+Once you've downloaded the model weights and placed them into the same directory as the `chat` or `chat.exe` executable, run:
+
+```
 ./chat
 ```
 
-You can download the weights for `ggml-alpaca-7b-q4.bin` with BitTorrent:
+The weights are based on the published fine-tunes from `alpaca-lora`, converted back into a pytorch checkpoint with a [modified script](https://github.com/tloen/alpaca-lora/pull/19) and then quantized with llama.cpp the regular way. 
+
+## Getting Started (13B)
 
-magnet: `magnet:?xt=urn:btih:5aaceaec63b03e51a98f04fd5c42320b2a033010&dn=ggml-alpaca-7b-q4.bin&tr=udp%3A%2F%2Ftracker.opentrackr.org%3A1337%2Fannounce&tr=udp%3A%2F%2Fopentracker.i2p.rocks%3A6969%2Fannounce`  
-torrent: https://btcache.me/torrent/5AACEAEC63B03E51A98F04FD5C42320B2A033010  
-torrent: https://torrage.info/torrent.php?h=5aaceaec63b03e51a98f04fd5c42320b2a033010  
+If you have more than 10GB of RAM, you can use the higher quality 13B `ggml-alpaca-13b-q4.bin` model. To download the weights, you can use
 
+```
 
-Alternatively you can download them with IPFS.
+# Any of these commands will work. 
+curl -o ggml-alpaca-13b-q4.bin -C - https://gateway.estuary.tech/gw/ipfs/Qme6wyw9MzqbrUMpFNVq42rC1kSdko7MGT9CL7o1u9Cv9G 
+curl -o ggml-alpaca-13b-q4.bin -C - https://ipfs.io/ipfs/Qme6wyw9MzqbrUMpFNVq42rC1kSdko7MGT9CL7o1u9Cv9G 
+curl -o ggml-alpaca-13b-q4.bin -C - https://cloudflare-ipfs.com/ipfs/Qme6wyw9MzqbrUMpFNVq42rC1kSdko7MGT9CL7o1u9Cv9G 
 
+# BitTorrent
+magnet:?xt=urn:btih:053b3d54d2e77ff020ebddf51dad681f2a651071&dn=ggml-alpaca-13b-q4.bin&tr=udp%3A%2F%2Ftracker.opentrackr.org%3A1337%2Fannounce&tr=udp%3A%2F%2Fopentracker.i2p.rocks%3A6969%2Fannounce&tr=udp%3A%2F%2Ftracker.openbittorrent.com%3A6969%2Fannounce&tr=udp%3A%2F%2F9.rarbg.com%3A2810%2Fannounce
+https://btcache.me/torrent/053B3D54D2E77FF020EBDDF51DAD681F2A651071  
+https://torrage.info/torrent.php?h=053b3d54d2e77ff020ebddf51dad681f2a651071
 ```
-# any of these will work
-curl -o ggml-alpaca-7b-q4.bin -C - https://gateway.estuary.tech/gw/ipfs/QmQ1bf2BTnYxq73MFJWu1B7bQ2UD6qG7D7YDCxhTndVkPC
-curl -o ggml-alpaca-7b-q4.bin -C - https://ipfs.io/ipfs/QmQ1bf2BTnYxq73MFJWu1B7bQ2UD6qG7D7YDCxhTndVkPC
-curl -o ggml-alpaca-7b-q4.bin -C - https://cloudflare-ipfs.com/ipfs/QmQ1bf2BTnYxq73MFJWu1B7bQ2UD6qG7D7YDCxhTndVkPC
+
+Once you've downloaded the weights, you can run the following command to enter chat
+
+```
+./chat -m ggml-alpaca-13b-q4.bin
 ```
 
-Save the `ggml-alpaca-7b-q4.bin` file in the same directory as your `./chat` executable. 
 
-The weights are based on the published fine-tunes from `alpaca-lora`, converted back into a pytorch checkpoint with a [modified script](https://github.com/tloen/alpaca-lora/pull/19) and then quantized with llama.cpp the regular way. 
+## Building from Source (MacOS/Linux)
+
+
+```sh
+git clone https://github.com/antimatter15/alpaca.cpp
+cd alpaca.cpp
+
+make chat
+./chat
+```
+
 
-## Windows Setup
+## Building from Source (Windows)
 
 - Download and install CMake: <https://cmake.org/download/>
 - Download and install `git`. If you've never used git before, consider a GUI client like <https://desktop.github.com/>
@@ -59,21 +91,6 @@ cmake --build . --config Release
 - (You can add other launch options like `--n 8` as preferred onto the same line)
 - You can now type to the AI in the terminal and it will reply. Enjoy!
 
-## 13B
-
-TODO: write more docs here (PRs welcome)
-
-You can download the weights for `ggml-alpaca-13b-q4.bin` with BitTorrent:
-
-magnet: `magnet:?xt=urn:btih:053b3d54d2e77ff020ebddf51dad681f2a651071&dn=ggml-alpaca-13b-q4.bin&tr=udp%3A%2F%2Ftracker.opentrackr.org%3A1337%2Fannounce&tr=udp%3A%2F%2Fopentracker.i2p.rocks%3A6969%2Fannounce&tr=udp%3A%2F%2Ftracker.openbittorrent.com%3A6969%2Fannounce&tr=udp%3A%2F%2F9.rarbg.com%3A2810%2Fannounce`  
-torrent: https://btcache.me/torrent/053B3D54D2E77FF020EBDDF51DAD681F2A651071  
-torrent: https://torrage.info/torrent.php?h=053b3d54d2e77ff020ebddf51dad681f2a651071
-
-
-```
-./chat -m ggml-alpaca-13b-q4.bin
-```
-
 ## Credit
 
 This combines [Facebook's LLaMA](https://github.com/facebookresearch/llama), [Stanford Alpaca](https://crfm.stanford.edu/2023/03/13/alpaca.html), [alpaca-lora](https://github.com/tloen/alpaca-lora) and [corresponding weights](https://huggingface.co/tloen/alpaca-lora-7b/tree/main) by Eric Wang (which uses [Jason Phang's implementation of LLaMA](https://github.com/huggingface/transformers/pull/21955) on top of Hugging Face Transformers), and [llama.cpp](https://github.com/ggerganov/llama.cpp) by Georgi Gerganov. The chat implementation is based on Matvey Soloviev's [Interactive Mode](https://github.com/ggerganov/llama.cpp/pull/61) for llama.cpp. Inspired by [Simon Willison's](https://til.simonwillison.net/llms/llama-7b-m2) getting started guide for LLaMA. [Andy Matuschak](https://twitter.com/andy_matuschak/status/1636769182066053120)'s thread on adapting this to 13B, using fine tuning weights by [Sam Witteveen](https://huggingface.co/samwit/alpaca13B-lora). 
